High-Stakes Decision-Making Within Complex Social Environments: A Computational Model of Belief Systems in the Arab Spring

Abstract

People experiencing similar conditions may make different decisions, and their belief systems provide insight about these differences. An example of high-stakes decision-making within a complex social context is the Arab Spring, in which large numbers of people decided to protest and even larger numbers decided to stay at home. This study uses qualitative analyses of interview narratives and social media addressing individual decisions to develop a computational model tracing the cognitive decision-making process. The model builds on work by Abelson and Carroll (1965), Schank and Abelson (a1977), and Axelrod (1976) to systematically trace the inferences connecting beliefs to decisions. The findings show that protest decisions were often based on positive emotions such as pride, hope, courage, and solidarity, triggered by beliefs about successful protest and self-sacrifice. By contrast, decisions to stay at home were triggered by beliefs about safety, state approval, and living conditions. As one participant said, “When I heard about the revolution in Tunisia, my heart was filled with solidarity for the people.” In the words of a non-participant: “When people are killed, we must be careful. There are more important things than protest: safety and stability.” This study of individual explanations about events identifies the role of emotions in high-stakes decision-making within complex social environments.